3 Reasons Universities are Using AI-Powered Explorance MLY for Qualitative Analysis

Written by Explorance.

Explorance MLY, formerly BlueML, is a revolutionary advancement in qualitative analysis. Powered by AI, this tool leverages machine learning models tailored for higher education institutions to distil actionable insights from vast quantities of unstructured student comments.

Explorance MLY features specialized models designed to identify sentiments, recommendations, and alerts within student qualitative comments, allowing institutions to act quickly. Facilitating data-informed decision-making empowers higher education institutions to significantly enhance the student experience. Analysis of these insights informs the development of teaching methods and course content, leading to higher student satisfaction, engagement, and academic success. The software also has specialized models built for the employee experience.

We spoke to four universities about their experiences using Explorance MLY and its qualitative analytics as they stepped up their work on the student voice during the 2023-24 academic year.

1. No more Manual Effort with Qualitative Analysis

Liverpool John Moores University (LJMU), which adopted Explorance Blue as its institutional platform for module evaluations nearly ten years ago, has added Explorance MLY to its student surveys toolkit for quality assurance and enhancement.

“Explorance MLY adds to our range of evaluation tools and, more importantly, it should provide access to rapid, automated analysis of open-text data that will support timely decision-making,” said Dr Phil Carey, Dean of the University’s Teaching & Learning Academy.

“The key benefit is that comment analysis can be provided in a more timely manner. We value the richness of insight that open-text comments provide and recognize that they are invaluable in helping us understand the student experience and respond to needs. Previously, the time-consuming nature of analysis could result in significant gaps between students providing comments and us being able to report on them.”

The University of Manchester has been working with Explorance since 2022 to develop its approach to unit evaluation surveys. It began implementing MLY last year after also experiencing issues analyzing open-ended comments.

“Working within such a massive university, we have always struggled to resource qualitative analysis,” revealed Jo Hicks, Teaching and Learning Manager (Programme Enhancement), who initially led the work with Explorance. “There has been nothing on the market to support this need, and using a data dictionary word check would take our strategic planning team weeks to derive anything meaningful from that.”

The University of Westminster is rolling out Explorance MLY to support student and employee surveys.

“We purchased MLY as a result of wanting to build on our qualitative analysis capabilities,” explained Kirsty Bryant, Senior Institutional Research Analyst – Strategy, Planning and Performance. “Before MLY, we would manually thematically analyze the open comments from just one of our surveys, despite running several large-scale surveys throughout the academic year. While we knew our dataset well, we were also aware of how resource-intensive such analysis was, so we were looking for ways to streamline this process to increase the amount of qualitative analysis that we could undertake.”

2. Deeper Understanding of Student Sentiments

LJMU was a key contributor to the initial development of Explorance MLY, providing institution-specific student comments to train the models along with other universities. Dr Carey pinpointed the potential for delving into demographic data.

“Having piloted MLY on several data sets, we can say that the software reliably identifies key themes and their sentiment background,” he said. “Categorization of topics is transparent, consistent, and can be traced back to the source. This means we can monitor changes in the landscape of student feedback over time and look at the longitudinal dynamics of specific themes or categories.

“Knowing that algorithms of the analysis are not static and that Explorance MLY will evolve, learn and adapt to changing themes has been one of the deciding factors in our decision to purchase MLY. Another advantage is that MLY is a standalone product, so we can use it to analyze a variety of open-text data sets from other external and internal surveys and evaluations. It is notable that Explorance welcomes ongoing user feedback, meaning that the UK higher education community is contributing to refining the instrument.”

Jo Hicks added: “At the University of Manchester, our students have consistently reported that whilst we give them lots of opportunities to provide feedback, they are less confident in our approach to telling them what we have done as a result. With MLY, we saw in the initial demonstration that qualitative analysis could be done in just 15 minutes and would give us that all-important story behind the metrics. Over time, I am sure this investment will give our institution more confidence in the data environment and the ability to understand different demographics.”<

And it’s not just the UK. Explorance MLY is also helping universities across the globe. “A key challenge we have encountered is managing bias in feedback,” commented Meagan Morrissey, Manager – Student and Staff Insights at the University of Newcastle, Australia.

“In the past, we have taken a rather costly yet effective approach to mitigating this issue by reading every student comment and removing destructive or offensive phrases. We look now to MLY to help us immediately categorize unstructured data and detect deviations from trends in feedback requiring further investigation. This will allow us to provide balanced, normalized scores with a reduced negative influence of bias related to gender, LGBTIQ identification, Aboriginal and Torres Strait Islander status and ethnicity.”

3. A Future-Proof Platform to Support Student Survey Strategy

The University of Manchester reported that with MLY and Explorance Blue, there was potential for other academic surveys to be delivered outside of the standard university window using the automation scheduling trigger. Pastoral and staff surveys may also be incorporated.

“We have definitely come a long way over the past two years – but there is still work to be done,” Jo explained. “Our original requirement through this process was to find a system that integrates with our student records system, one that would provide more automation for our unit surveys and allow us to be more flexible and agile, giving us the data quickly to make decisions. MLY is usable, efficient, and future-proof, and it will help us close the feedback loop. It will be an important tool in the work of the University’s newly-formed Student Surveys Strategy Group, which is reviewing future processes.”

At the University of Westminster, Kirsty revealed that, in addition to offering “quick deductive thematic analysis,” MLY was a valuable platform for enabling wider innovation in her team.

“The Artificial Intelligence through Explorance MLY gives us greater capacity so we can run all our major surveys through this system and will enable us to be more responsive, especially in consideration of module evaluation surveys, where we can identify in-year issues and react quickly,” she continued.

“We also expect there to be a culture shift in how my team spends their time. We can focus on how and what we communicate to stakeholders and ensure accountability in making positive change. We will be able to share high-level analysis of the open comments almost as quickly as we currently deliver the quantitative counterparts of our surveys. We expect this to be a real culture change, as our qualitative data can be elevated to the same status as our extensive quantitative datasets.​”

Meagan concurred: “This partnership with MLY will enable us to better support our teachers, identify our outstanding teachers more accurately, and track themes in student voice. We look forward to creating an environment where our academic staff are more independently engaged in the feedback process, see their impact on their students, and are supported to achieve the University’s vision for the future.”

Join us for our AI-expert panel on ‘Unlocking the power of open-ended student feedback for better decision making’ as part of the Student Voices in Higher Education conference at BMA House in London on 16-17 April

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